Works matching AU Entezami, Alireza
Results: 27
On continuous health monitoring of bridges under serious environmental variability by an innovative multi-task unsupervised learning method.
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- Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance, 2024, v. 20, n. 12, p. 1975, doi. 10.1080/15732479.2023.2166538
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- Article
Damage localization under ambient excitations and non-stationary vibration signals by a new hybrid algorithm for feature extraction and multivariate distance correlation methods.
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- European Journal of Industrial Relations, 2019, v. 25, n. 1, p. 347, doi. 10.1177/1475921718754372
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- Article
Artificial Intelligence-Powered Computational Strategies in Selecting and Augmenting Data for Early Design of Tall Buildings with Outer Diagrids.
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- Buildings (2075-5309), 2024, v. 14, n. 4, p. 1118, doi. 10.3390/buildings14041118
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Machine learning‐aided prediction of windstorm‐induced vibration responses of long‐span suspension bridges.
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- Computer-Aided Civil & Infrastructure Engineering, 2025, v. 40, n. 8, p. 1043, doi. 10.1111/mice.13387
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- Article
Investigation of Temperature Effects into Long-Span Bridges via Hybrid Sensing and Supervised Regression Models.
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- Remote Sensing, 2023, v. 15, n. 14, p. 3503, doi. 10.3390/rs15143503
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- Article
Elimination of Thermal Effects from Limited Structural Displacements Based on Remote Sensing by Machine Learning Techniques.
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- Remote Sensing, 2023, v. 15, n. 12, p. 3095, doi. 10.3390/rs15123095
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- Article
Online Hybrid Learning Methods for Real-Time Structural Health Monitoring Using Remote Sensing and Small Displacement Data.
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- Remote Sensing, 2022, v. 14, n. 14, p. N.PAG, doi. 10.3390/rs14143357
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- Article
Application of supervised learning to validation of damage detection.
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- Archive of Applied Mechanics, 2021, v. 91, n. 1, p. 393, doi. 10.1007/s00419-020-01779-z
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Unsupervised data normalization for continuous dynamic monitoring by an innovative hybrid feature weighting-selection algorithm and natural nearest neighbor searching.
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- Structural Health Monitoring, 2023, v. 22, n. 6, p. 4005, doi. 10.1177/14759217231166116
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- Article
Non-parametric empirical machine learning for short-term and long-term structural health monitoring.
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- Structural Health Monitoring, 2022, v. 21, n. 6, p. 2700, doi. 10.1177/14759217211069842
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- Article
A novel data-driven method for structural health monitoring under ambient vibration and high-dimensional features by robust multidimensional scaling.
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- Structural Health Monitoring, 2021, v. 20, n. 5, p. 2758, doi. 10.1177/1475921720973953
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- Article
Fast unsupervised learning methods for structural health monitoring with large vibration data from dense sensor networks.
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- Structural Health Monitoring, 2020, v. 19, n. 6, p. 1685, doi. 10.1177/1475921719894186
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- Article
Data-driven damage diagnosis under environmental and operational variability by novel statistical pattern recognition methods.
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- Structural Health Monitoring, 2019, v. 18, n. 5/6, p. 1416, doi. 10.1177/1475921718800306
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- Article
Damage localization under ambient excitations and non-stationary vibration signals by a new hybrid algorithm for feature extraction and multivariate distance correlation methods.
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- Structural Health Monitoring, 2019, v. 18, n. 2, p. 347, doi. 10.1177/1475921718754372
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- Article
An unsupervised learning approach by novel damage indices in structural health monitoring for damage localization and quantification.
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- Structural Health Monitoring, 2018, v. 17, n. 2, p. 325, doi. 10.1177/1475921717693572
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- Article
A Comparative Study on Structural Displacement Prediction by Kernelized Regressors under Limited Training Data †.
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- Engineering Proceedings, 2023, v. 58, p. 57, doi. 10.3390/ecsa-10-16031
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- Article
Regression Tree Ensemble to Forecast Thermally Induced Responses of Long-Span Bridges †.
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- Engineering Proceedings, 2023, v. 58, p. 56, doi. 10.3390/ecsa-10-16030
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- Article
A Parsimonious Yet Robust Regression Model for Predicting Limited Structural Responses of Remote Sensing †.
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- Engineering Proceedings, 2023, v. 58, p. 54, doi. 10.3390/ecsa-10-16028
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- Article
Structural Damage Detection in the Wooden Bridge Using the Fourier Decomposition, Time Series Modeling and Machine Learning Methods.
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- Journal of Soft Computing in Civil Engineering, 2024, v. 8, n. 2, p. 83, doi. 10.22115/SCCE.2023.401971.1669
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- Article
Detection of Partially Structural Collapse Using Long-Term Small Displacement Data from Satellite Images.
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- Sensors (14248220), 2022, v. 22, n. 13, p. 4964, doi. 10.3390/s22134964
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- Article
Damage Detection in Largely Unobserved Structures under Varying Environmental Conditions: An AutoRegressive Spectrum and Multi-Level Machine Learning Methodology.
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- Sensors (14248220), 2022, v. 22, n. 4, p. N.PAG, doi. 10.3390/s22041400
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- Article
Health Monitoring of Large-Scale Civil Structures: An Approach Based on Data Partitioning and Classical Multidimensional Scaling.
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- Sensors (14248220), 2021, v. 21, n. 5, p. 1646, doi. 10.3390/s21051646
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Big Data Analytics and Structural Health Monitoring: A Statistical Pattern Recognition-Based Approach.
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- Sensors (14248220), 2020, v. 20, n. 8, p. 2328, doi. 10.3390/s20082328
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An iterative order determination method for time-series modeling in structural health monitoring.
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- Advances in Structural Engineering, 2018, v. 21, n. 2, p. 300, doi. 10.1177/1369433217717118
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- Article
Ensemble learning‐based structural health monitoring by Mahalanobis distance metrics.
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- Structural Control & Health Monitoring, 2021, v. 28, n. 2, p. 1, doi. 10.1002/stc.2663
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A sensitivity‐based finite element model updating based on unconstrained optimization problem and regularized solution methods.
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- Structural Control & Health Monitoring, 2020, v. 27, n. 5, p. 1, doi. 10.1002/stc.2481
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Experimental Investigation on the Seismic Behavior of RC Double‐Column Medium‐Height Bents Retrofitted With SCEB‐Us.
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- Earthquake Engineering & Structural Dynamics, 2025, v. 54, n. 3, p. 925, doi. 10.1002/eqe.4288
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- Article